Electrical Engineering Wroclaw University of Technology

Electrical Engineering Wroclaw University of Technology 10 records found  Search took 0.03 seconds. 
1. Automatic Fault Classification in Power Electronics Using Time-Frequency Distribution and Neural Networks / Leonowicz, Z ; Lobos, T [RZ I07/2003/I-077] [ENY-ARTICLE-2009-249]
A new method of fault analysis and detection by signal classification in frequency converters is presented. [...]
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2. Automated Classification of Power Quality Disturbances using SVM and RBF Networks / Janik, P ; Lobos, T [ENY-ARTICLE-2009-239]
The authors propose a new method of power quality classification using SVM (Support Vector Machine) neural networks. [...]
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3. Analysis of influence of power quality disturbances using a neuro-fuzzy systems / Janik, P ; Leonowicz, Z ; Lobos, T ; Waclawek, Z [RZ I07/2007/I-025] [ENY-ARTICLE-2008-172]
The authors propose an automated neuro-fuzzy system approach (with neural network subsystem) to power quality assessment incorporating equipment susceptibility patterns. [...]
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4. Adaptive and intelligent systems for generator monitoring and protection purposes / Rebizant, W ; Szafran, J ; Lee, S J ; Kang, S H [ENY-ARTICLE-2008-148]
New adaptive scheme for signal parameter measurement for generator monitoring and protection is presented. [...]
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5. Current Transformer Saturation Detection with Genetically Optimized Neural Networks / Rebizant, W ; Bejmert, D [ENY-ARTICLE-2008-146]
Application of the genetic algorithm (GA) for optimization of artificial neural network (ANN) based CT saturation detector is presented. [...]
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6. Neural networks for real-time estimation of parameters of signals in power systems / Cichocki, A ; Kostyla, P ; Lobos, T ; Waclawek, Z [I07/1994/I-184] [ENY-ARTICLE-2008-087]
Fast determination of parameters of the fundamental waveform of voltages and currents is essential for the control and protection of electrical power systems. [...]
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7. Neural networks for real-time estimation of parameters of signals in power systems / Cichocki, A ; Kostyla, P ; Lobos, T ; Waclawek, Z [I07/1999/I-402] [ENY-ARTICLE-2008-068]
The purpose of this paper is to present new algorithms and along with them new architectures of analogue neuron-like adaptive processors for online estimation of parameters of sinusoidal signals, which are distorted by higher harmonics and corrupted by noise. [...]
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8. Adaptive Neural Networks for Robust Estimation of parameters of Noisy Harmonic Signals / Cichocki, A ; Kostyla, P ; Lobos, T ; Waclawek, Z [I07/96/I-278] [ENY-ARTICLE-2008-054]
In many applications, very fast methods are required for estimating and measurement of parameters of harmonic signals distorted by noise. [...]
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9. Independent Variable Selection: An Application of Independent Component Analysis to Forecasting a Stock Index / Cichocki, A ; Stansell, S R ; Leonowicz, Z ; Buck, J [ENY-PREPRINT-2008-002]
Forecasts of financial time series requires the use of a possibly large set of input (explanatory) variables drawn form a very large set of potential inputs. [...]
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10. Real-Time Parameter Estimation of Signals in Converter Fed Drives using Adaptive Neural Networks / Lobos, T ; Koglin, H J ; Waclawek, Z [ENY-ARTICLE-2008-031]
Frequency converter-fed induction motor drives were simulated using the EMTP-ATP (Electromagnetic Transients Program - Alternative Transients Program) The aim of the simulation investigations is to develop a feasible method for drive visualisation and for diagnosis of different unsymmetrical operations. [...]
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